Pattern Recognition of EEG Signal during Motor Imagery by Using SOM

Electroencephalograph (EEG) recordings during right and left hand motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by e.g., handicap users with amyotrophic lateral sclerosis (ALS). The conventional method purposes the recognition of right hand and left hand motor imagery. In this paper, feature extraction based on Self Organizing Maps (SOM) using auto-regressive (AR) spectrum was introduced to discriminate the EEG signals recorded during right hand, left hand and foot motor imagery. The features in pattern recognition are discussed through the experimental studies.